A series of feature extraction algorithms based on locality preserving projection have been proposed.PCA algorithm must be firstly used for high-dimensional samples when these algorithms are applied in face recognition.Therefore,by using the orthogonal discriminant locality preserving projection algorithm,a direct orthogonal discriminant locality preserving projection algorithm is proposed.Through the corresponding matrix decomposition according to the properties of the Laplacian matrix,the projection matrix can be directly extracted from the original high-dimensional space without using PCA algorithm as the first step.In order to solve the small sample size problem,the null space of the local within-class scatter matrix is obtained and the between-class scatter matrix is maximized.Experimental results on face database demonstrate the effectiveness of the proposed method.